1. Field of the Invention
The present invention pertains to the field of disk drives, and more particularly to a method for applying an adaptive seeking algorithm to a removable cartridge disk file with excessive repeatable runout.
2. Background
In a removable cartridge disk drive, the read/write heads, or transducers, of the drive must float directly above the centerline of any data track being accessed on the surface of the disk contained in the cartridge. Mechanical imperfections and geometric constraints cause the transducers to stray from track center, giving rise to a phenomenon known in the industry as repetitive runout. Repetitive runout occurs for several reasons, including repeatable bearing runout, imbalance between the rotating hub assembly and the disk, and disk clamping errors. Disk clamping errors, for example, are specific to removable media disk drives.
Imperfections such as the above create a variance between the center of the hub on which the disk sits and the center of rotation of the disk.. This gives rise to a repeatable tracking error at the rotational frequency. Additionally, in a disk drive with a rotary actuator arm, the repeatable runout magnitude and phase vary with the position of the actuator arm. Further, repeatable runout can be time variant because the aforementioned imbalances can change or the disk can slip during normal operation.
Conventional disk drives use digital servos with high bandwidths to compensate for repetitive runout. This is effective for runout on the order of a fraction of a track. However, removable cartridge disk drives generally experience runout approaching several tracks. This is known as excessive repeatable runout. The conventional servo cannot compensate for excessive repeatable runout without sacrificing seeking performance.
A least mean square technique has been used to adjust tap weights for every servo sample based on the measured position signal. The method requires sine and cosine functions for tap weight adjustment and feed forward control signal calculation. Approximately one revolution of the disk is required for the tap weights to be adapted to the correct values for minimizing tracking error so that the drive can perform read/write operations. However, the runout adaptation time increases the settling time, causing access time to double. Moreover, the method alleviates track following error only; it ignores track seeking performance.
Another known technique is to use discrete Fourier transforms (DFTs) to identify the magnitude and phase of the repeatable runout. During calibration the microprocessor collects the position-error-signal data for several revolutions. The DFT calculation is then performed and the results are used to form the repeatable runout correction signal, which is stored for subsequent use during normal operations. The DFT procedure can be repeated continuously while the drive is track following and not engaged in read/write functions. The disadvantage of this technique is that it is slow, requiring several revolutions to derive the repeatable runout correction signal. The technique is also calculation intensive. A typical disk drive with sixty servo sectors per revolution requires 120 multipliers and 119 adders to generate the DFT results from one revolution of the position-error-signal data. This mandates that an expensive microprocessor be used--an inadequate solution in the competitive disk drive industry.
Alternatively, a slower microprocessor could be used with the DFT calculation performed only at selected tracks; the DFT results would then be used to form the feed forward signal during normal operation. This technique would compensate for runout error dependent on the actuator position. However, the time-variant runout could not be addressed because the DFT would be based on prior runout information.
Another known method increases the typical disk drive state estimator from a third-order to a fifth-order model, which includes not only head position, head velocity, and bias torque, but also first and second runout states. The fifth-order state estimator can be used in either a hybrid runout compensator technique or a real time state space technique. In the hybrid technique, the fifth-order estimator is used during calibration to obtain runout correction values, which are stored in random access memory to be used in subsequent read/write operations. Because the fifth-order estimator is not used during normal operation, the dynamic can be selected to be relatively slow to avoid undue sensitivity of the estimator's performance due to the uncertainty in the measured position. The hybrid technique is less calculation-intensive than the DFT method, but it too is slow and unadaptive.
The real time state space technique is adaptive, but the fifth-order state estimator model is highly sensitive to noise. As the head moves across the track boundary during seeking, the error in the measured position can approach one-half of the track width--typically higher than the runout magnitude without correction. At least one-half of a revolution would have to take place before the runout magnitude and phase could be compensated for.
Another disadvantage of a fifth-order estimator is that the model attempts to estimate the unknown runout and bias torque simultaneously, using only one input: the estimator error. This disadvantage can be overcome by choosing fast estimator poles for estimated position, velocity, and first and second runout states, but using a slower estimator pole for the estimated bias torque. However, such a design is inappropriate for the typical disk drive servo, which must perform well under a wide variety of conditions. For example, if the actuator bearing were to hit a small particle during arrival at the target track, the transient response--which is dominated by the bias estimator pole--would be too slow.
Another disadvantage of a fifth-order estimator model is that the extra calculation required (as compared to a conventional third-order model) generates more quantization error and reduces system throughput. This would be problematic in the disk drive industry because the typical low-cost disk drive uses only one microprocessor to process both servo and interface controller codes.
Based on the foregoing, there is a need for a method of calibration and seeking that (1) modifies the control signal during seeking, (2) determines the runout magnitude and phase at various tracks, and (3) compensates for the relative magnitude and phase variations between the originated and target tracks.